Empty Index#

Building the Empty Index

Empty Index.

class llama_index.core.indices.empty.EmptyIndex(index_struct: Optional[EmptyIndexStruct] = None, service_context: Optional[ServiceContext] = None, **kwargs: Any)#

Empty Index.

An index that doesn’t contain any documents. Used for pure LLM calls. NOTE: this exists because an empty index it allows certain properties, such as the ability to be composed with other indices + token counting + others.

build_index_from_nodes(nodes: Sequence[BaseNode]) IS#

Build the index from nodes.

delete_nodes(node_ids: List[str], delete_from_docstore: bool = False, **delete_kwargs: Any) None#

Delete a list of nodes from the index.

Parameters

doc_ids (List[str]) – A list of doc_ids from the nodes to delete

delete_ref_doc(ref_doc_id: str, delete_from_docstore: bool = False, **delete_kwargs: Any) None#

Delete a document and it’s nodes by using ref_doc_id.

classmethod from_documents(documents: Sequence[Document], storage_context: Optional[StorageContext] = None, show_progress: bool = False, callback_manager: Optional[CallbackManager] = None, transformations: Optional[List[TransformComponent]] = None, service_context: Optional[ServiceContext] = None, **kwargs: Any) IndexType#

Create index from documents.

Parameters

documents (Optional[Sequence[BaseDocument]]) – List of documents to build the index from.

property index_id: str#

Get the index struct.

insert(document: Document, **insert_kwargs: Any) None#

Insert a document.

insert_nodes(nodes: Sequence[BaseNode], **insert_kwargs: Any) None#

Insert nodes.

property ref_doc_info: Dict[str, RefDocInfo]#

Retrieve a dict mapping of ingested documents and their nodes+metadata.

refresh(documents: Sequence[Document], **update_kwargs: Any) List[bool]#

Refresh an index with documents that have changed.

This allows users to save LLM and Embedding model calls, while only updating documents that have any changes in text or metadata. It will also insert any documents that previously were not stored.

refresh_ref_docs(documents: Sequence[Document], **update_kwargs: Any) List[bool]#

Refresh an index with documents that have changed.

This allows users to save LLM and Embedding model calls, while only updating documents that have any changes in text or metadata. It will also insert any documents that previously were not stored.

set_index_id(index_id: str) None#

Set the index id.

NOTE: if you decide to set the index_id on the index_struct manually, you will need to explicitly call add_index_struct on the index_store to update the index store.

Parameters

index_id (str) – Index id to set.

update(document: Document, **update_kwargs: Any) None#

Update a document and it’s corresponding nodes.

This is equivalent to deleting the document and then inserting it again.

Parameters
  • document (Union[BaseDocument, BaseIndex]) – document to update

  • insert_kwargs (Dict) – kwargs to pass to insert

  • delete_kwargs (Dict) – kwargs to pass to delete

update_ref_doc(document: Document, **update_kwargs: Any) None#

Update a document and it’s corresponding nodes.

This is equivalent to deleting the document and then inserting it again.

Parameters
  • document (Union[BaseDocument, BaseIndex]) – document to update

  • insert_kwargs (Dict) – kwargs to pass to insert

  • delete_kwargs (Dict) – kwargs to pass to delete

class llama_index.core.indices.empty.EmptyIndexRetriever(index: EmptyIndex, input_prompt: Optional[BasePromptTemplate] = None, callback_manager: Optional[CallbackManager] = None, **kwargs: Any)#

EmptyIndex query.

Passes the raw LLM call to the underlying LLM model.

Parameters

input_prompt (Optional[BasePromptTemplate]) – A Simple Input Prompt (see Prompt Templates).

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) QueryComponent#

Get query component.

get_prompts() Dict[str, BasePromptTemplate]#

Get a prompt.

get_service_context() Optional[ServiceContext]#

Attempts to resolve a service context. Short-circuits at self.service_context, self._service_context, or self._index.service_context.

retrieve(str_or_query_bundle: Union[str, QueryBundle]) List[NodeWithScore]#

Retrieve nodes given query.

Parameters

str_or_query_bundle (QueryType) – Either a query string or a QueryBundle object.

update_prompts(prompts_dict: Dict[str, BasePromptTemplate]) None#

Update prompts.

Other prompts will remain in place.

llama_index.core.indices.empty.GPTEmptyIndex#

alias of EmptyIndex